Skeleton clustering by autonomous mobile robots for subtle fall risk discovery

Yutaka Deguchi, Einoshin Suzuki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

In this paper, we propose two new instability features, a data pre-processing method, and a new evaluation method for skeleton clustering by autonomous mobile robots for subtle fall risk discovery. We had proposed an autonomous mobile robot which clusters skeletons of a monitored person for distinct fall risk discovery and achieved promising results. A more natural setting posed us problems such as ambiguities in class labels and low discrimination power of our original instability features between safe/unsafe skeletons. We validate our three new proposals through evaluation by experiments.

Original languageEnglish
Title of host publicationFoundations of Intelligent Systems - 21st International Symposium, ISMIS 2014, Proceedings
PublisherSpringer Verlag
Pages500-505
Number of pages6
ISBN (Print)9783319083254
DOIs
Publication statusPublished - Jan 1 2014
Event21st International Symposium on Methodologies for Intelligent Systems, ISMIS 2014 - Roskilde, Denmark
Duration: Jun 25 2014Jun 27 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8502 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other21st International Symposium on Methodologies for Intelligent Systems, ISMIS 2014
CountryDenmark
CityRoskilde
Period6/25/146/27/14

Fingerprint

Autonomous Mobile Robot
Skeleton
Mobile robots
Clustering
Labels
Data Preprocessing
Evaluation Method
Discrimination
Person
Processing
Distinct
Experiments
Evaluation
Experiment

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Deguchi, Y., & Suzuki, E. (2014). Skeleton clustering by autonomous mobile robots for subtle fall risk discovery. In Foundations of Intelligent Systems - 21st International Symposium, ISMIS 2014, Proceedings (pp. 500-505). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8502 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-319-08326-1_51

Skeleton clustering by autonomous mobile robots for subtle fall risk discovery. / Deguchi, Yutaka; Suzuki, Einoshin.

Foundations of Intelligent Systems - 21st International Symposium, ISMIS 2014, Proceedings. Springer Verlag, 2014. p. 500-505 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8502 LNAI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Deguchi, Y & Suzuki, E 2014, Skeleton clustering by autonomous mobile robots for subtle fall risk discovery. in Foundations of Intelligent Systems - 21st International Symposium, ISMIS 2014, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8502 LNAI, Springer Verlag, pp. 500-505, 21st International Symposium on Methodologies for Intelligent Systems, ISMIS 2014, Roskilde, Denmark, 6/25/14. https://doi.org/10.1007/978-3-319-08326-1_51
Deguchi Y, Suzuki E. Skeleton clustering by autonomous mobile robots for subtle fall risk discovery. In Foundations of Intelligent Systems - 21st International Symposium, ISMIS 2014, Proceedings. Springer Verlag. 2014. p. 500-505. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-08326-1_51
Deguchi, Yutaka ; Suzuki, Einoshin. / Skeleton clustering by autonomous mobile robots for subtle fall risk discovery. Foundations of Intelligent Systems - 21st International Symposium, ISMIS 2014, Proceedings. Springer Verlag, 2014. pp. 500-505 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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